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Semantic Segmentation

Papers

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Showing 11651–11700 of 14763 papers

TitleStatusHype
Uncertainty-Calibrated Test-Time Model Adaptation without Forgetting—0
Uncertainty Driven Active Learning for Image Segmentation in Underwater Inspection—0
Uncertainty, Edge, and Reverse-Attention Guided Generative Adversarial Network for Automatic Building Detection in Remotely Sensed Images—0
Uncertainty-Error correlations in Evidential Deep Learning models for biomedical segmentation—0
Uncertainty estimates for semantic segmentation: providing enhanced reliability for automated motor claims handling—0
Uncertainty Estimation and Out-of-Distribution Detection for LiDAR Scene Semantic Segmentation—0
Uncertainty estimation in Deep Learning for Panoptic segmentation—0
Uncertainty Estimation in Instance Segmentation with Star-convex Shapes—0
Uncertainty Gated Network for Land Cover Segmentation—0
Uncertainty-guided Model Generalization to Unseen Domains—0
Uncertainty-Guided Mutual Consistency Learning for Semi-Supervised Medical Image Segmentation—0
Uncertainty guided semi-supervised segmentation of retinal layers in OCT images—0
Uncertainty Modeling in Ultrasound Image Segmentation for Precise Fetal Biometric Measurements—0
Uncertainty Quantification for Bird's Eye View Semantic Segmentation: Methods and Benchmarks—0
Uncertainty Quantification for Eosinophil Segmentation—0
Uncertainty Quantification in Machine Learning Based Segmentation: A Post-Hoc Approach for Left Ventricle Volume Estimation in MRI—0
Uncertainty Quantification in Medical Image Segmentation with Multi-decoder U-Net—0
UNCERTAINTY QUANTIFICATION USING VARIATIONAL INFERENCE FOR BIOMEDICAL IMAGE SEGMENTATION—0
Deep Learning with Uncertainty Quantification for Predicting the Segmentation Dice Coefficient of Prostate Cancer Biopsy Images—0
Self-Supervised 3D Traversability Estimation with Proxy Bank Guidance—0
Uncertainty Reduction for Model Adaptation in Semantic Segmentation—0
Understanding Deep Learning Techniques for Image Segmentation—0
Understanding Fine-tuning CLIP for Open-vocabulary Semantic Segmentation in Hyperbolic Space—0
Understanding Human-Centric Images: From Geometry to Fashion—0
Understanding Imbalanced Semantic Segmentation Through Neural Collapse—0
Understanding Important Features of Deep Learning Models for Transmission Electron Microscopy Image Segmentation—0
Understanding Neural Pathways in Zebrafish through Deep Learning and High Resolution Electron Microscope Data—0
Understanding Segment Anything Model: SAM is Biased Towards Texture Rather than Shape—0
Understanding Self-Supervised Features for Learning Unsupervised Instance Segmentation—0
Understanding the Challenges When 3D Semantic Segmentation Faces Class Imbalanced and OOD Data—0
Understanding the Effect of using Semantically Meaningful Tokens for Visual Representation Learning—0
Understanding Video Transformers via Universal Concept Discovery—0
Understand Scene Categories by Objects: A Semantic Regularized Scene Classifier Using Convolutional Neural Networks—0
UNet-2022: Exploring Dynamics in Non-isomorphic Architecture—0
UNet-3D with Adaptive TverskyCE Loss for Pancreas Medical Image Segmentation—0
U-Net and its variants for medical image segmentation: theory and applications—0
U-Net and its variants for Medical Image Segmentation : A short review—0
UNet++ and LSTM combined approach for Breast Ultrasound Image Segmentation—0
UNet#: A UNet-like Redesigning Skip Connections for Medical Image Segmentation—0
U-Net Based Architecture for an Improved Multiresolution Segmentation in Medical Images—0
U-Net Based Multi-instance Video Object Segmentation—0
UNet Based Pipeline for Lung Segmentation from Chest X-Ray Images—0
U-Net Ensemble for Enhanced Semantic Segmentation in Remote Sensing Imagery—0
U-Net in Medical Image Segmentation: A Review of Its Applications Across Modalities—0
U-Netmer: U-Net meets Transformer for medical image segmentation—0
U-NetMN and SegNetMN: Modified U-Net and SegNet models for bimodal SAR image segmentation—0
U-Nets as Belief Propagation: Efficient Classification, Denoising, and Diffusion in Generative Hierarchical Models—0
U-net super-neural segmentation and similarity calculation to realize vegetation change assessment in satellite imagery—0
U-Net Training with Instance-Layer Normalization—0
U-Net Using Stacked Dilated Convolutions for Medical Image Segmentation—0
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All datasetsADE20KNYU-Depth V2Cityscapes testCityscapes valADE20K valPASCAL ContextS3DIS Area5PASCAL VOC 2012 testS3DISScanNetSUN-RGBDDensePASS

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1InternImage-H (M3I Pre-training)Params (M)1,310—Unverified
2ViT-P (InternImage-H)Validation mIoU63.6—Unverified
3ONE-PEACEValidation mIoU63—Unverified
4InternImage-HValidation mIoU62.9—Unverified
5M3I Pre-training (InternImage-H)Validation mIoU62.9—Unverified
6BEiT-3Validation mIoU62.8—Unverified
7EVAValidation mIoU62.3—Unverified
8ViT-P (OneFormer, InternImage-H)Validation mIoU61.6—Unverified
9ViT-Adapter-L (Mask2Former, BEiTv2 pretrain)Validation mIoU61.5—Unverified
10FD-SwinV2-GValidation mIoU61.4—Unverified